LAUSR

Depressive disorders among college students are a significant public health issue. Most existing studies on factors related to depressive disorders use traditional linear regression models, which have limited ability to reveal deeper insights. This study aims to explore the complexities of depressive disorders further by applying quantile regression. The study was conducted at six universities in China from November 26 to December 6, 2022, using a cross-sectional questionnaire survey with a cluster sampling design. The questionnaire includes the Patient Health Questionnaire-9, the Interpersonal Sensitivity subscale of the Symptom Checklist-90, the Positive Psychological Capital Questionnaire, and the Perceived Social Support Scale. Data analysis was performed using quantile regression with SPSS 26.0. A total of 3,156 college students participated, and 2,580 valid questionnaires were collected. The prevalence of depressive disorders was 22.4%. Quantile regression indicated that depressive disorders were linked to social support (β 25th = -0.044, β 50th = -0.111, β 75th = -0.244, p < 0.001), interpersonal sensitivity (β25th = 0.073, β50th = 0.127, β75th = 0.232, p < 0.001), psychological capital (β 25th= -0.077, β 50th = -0.154, β 75th = -0.252, p < 0.001), and regular contact with family (β 25th = -0.057, p < 0.05). Social support and psychological capital showed negative associations with depressive disorders, while interpersonal sensitivity had a positive association. The strength of these correlations varied across quartiles, with social support, psychological capital, and interpersonal sensitivity being more strongly associated with depressive disorders at higher quartile points. This study identifies the factors influencing college students with varying levels of depressive disorders. Students with severe depression tend to exhibit higher levels of interpersonal sensitivity, psychological capital, and social support. Percentile analysis helps to explore mental health issues more thoroughly, providing valuable details for targeted intervention.